A new Russell model for selecting suppliers

Abstract

Recently, supply chain management (SCM) has been considered by many researchers. Supplier evaluation and selection plays a significant role in establishing an effective SCM. One of the techniques that can be used for selecting suppliers is data envelopment analysis (DEA). In some situations, to select suitable suppliers, purchasing managers deal with undesirable outputs, dual-role factors and imprecise data. The objective of this paper is to propose a new Russell model for selecting the best suppliers in the presence of undesirable outputs, dual-role factors and imprecise data. A case study demonstrates the application of the proposed method.

abstract = "Recently, supply chain management (SCM) has been considered by many researchers. Supplier evaluation and selection plays a significant role in establishing an effective SCM. One of the techniques that can be used for selecting suppliers is data envelopment analysis (DEA). In some situations, to select suitable suppliers, purchasing managers deal with undesirable outputs, dual-role factors and imprecise data. The objective of this paper is to propose a new Russell model for selecting the best suppliers in the presence of undesirable outputs, dual-role factors and imprecise data. A case study demonstrates the application of the proposed method.",

N2 - Recently, supply chain management (SCM) has been considered by many researchers. Supplier evaluation and selection plays a significant role in establishing an effective SCM. One of the techniques that can be used for selecting suppliers is data envelopment analysis (DEA). In some situations, to select suitable suppliers, purchasing managers deal with undesirable outputs, dual-role factors and imprecise data. The objective of this paper is to propose a new Russell model for selecting the best suppliers in the presence of undesirable outputs, dual-role factors and imprecise data. A case study demonstrates the application of the proposed method.

AB - Recently, supply chain management (SCM) has been considered by many researchers. Supplier evaluation and selection plays a significant role in establishing an effective SCM. One of the techniques that can be used for selecting suppliers is data envelopment analysis (DEA). In some situations, to select suitable suppliers, purchasing managers deal with undesirable outputs, dual-role factors and imprecise data. The objective of this paper is to propose a new Russell model for selecting the best suppliers in the presence of undesirable outputs, dual-role factors and imprecise data. A case study demonstrates the application of the proposed method.